Motion compensation for aortic valves using partial angle CT reconstructions

Purpose A motion compensation method that is aimed at correcting motion artifacts of cardiac valves is proposed. The primary focus is the aortic valve. Methods The method is based around partial angle reconstructions and a cost function including the image entropy. A motion model is applied to approximate the cardiac motion in the temporal and spatial domain. Based on characteristic values for velocities and strain during cardiac motion, penalties for the velocity and spatial derivatives are introduced to maintain anatomically realistic motion vector fields and avoid distortions. The model addresses global elastic deformation, but not the finer and more complicated motion of the valve leaflets. Results The method is verified based on clinical data. Image quality was improved for most artifact-impaired reconstructions. An image quality study with Likert scoring of the motion artifact severity on a scale from 1 (highest image quality) to 5 (lowest image quality/extreme artifact presence) was performed. The biggest improvements after applying motion compensation were achieved for strongly artifact-impaired initial images scoring 4 and 5, resulting in an average change of the scores by -0.59 +/- 0.06$-0.59\pm 0.06$ and -1.33 +/- 0.03$-1.33\pm 0.03$, respectively. In the case of artifact-free images, a chance to introduce blurring was observed and their average score was raised by 0.42 +/- 0.03. Conclusion Motion artifacts were consistently removed and image quality improved.

Automated summary

This study proposes a motion compensation method for correcting motion artifacts of cardiac valves. The method utilizes partial angle reconstructions and a cost function incorporating image entropy to approximate cardiac motion. By introducing characteristic values and penalties for velocity and spatial derivatives, the method maintains anatomically realistic motion fields. The results show consistent removal of motion artifacts and improved image quality.